R: Bayesian Variable Selection and Model Choice for Generalized Additive Mixed Models

# Bayesian Variable Selection and Model Choice for Generalized Additive Mixed Models

## Documentation for package ‘spikeSlabGAM’ version 1.1-20

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

evalTerm | Get summaries of the posterior (predictive) distribution of the linear predictor of a model term
fct | Generate design for a factor covariate
getPosteriorTerm | Get the posterior distribution of the linear predictor of a model term
lin | Generate orthogonal polynomial base for a numeric covariate without intercept
mrf | Generate design for a 2-D Gaussian Markov Random Field
plot.spikeSlabGAM | Generates graphical summaries of a fitted model
plotTerm | Plot the estimated effect of a model term.
predict.spikeSlabGAM | Obtain posterior predictive/credible intervals from a spike-and-slab model
print.summary.spikeSlabGAM | Print summary for posterior of a 'spikeSlabGAM' fit
rnd | Generate design for a random intercept
sm | Generate a reparameterized P-spline base
spikeAndSlab | Set up and sample a spike-and-slab prior model.
spikeSlabGAM | Generate posterior samples for a GAMM with spike-and-slab priors
srf | Generate design for penalized surface estimation.
ssGAM2Bugs | Convert samples from a model fitted with 'spikeSlabGAM' into a 'bugs'-object
ssGAMDesign | Generate design and model information for 'spikeSlabGAM'
summary.spikeSlabGAM | Summary for posterior of a 'spikeSlabGAM' fit
u | Generate design for an always included covariate